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Method and device for rapid identification of small fault of coal seam

A technology of small faults and coal seams, applied in the field of geological exploration, can solve the problems of inability to observe, understand, analyze, leak small faults and small structures, and small structures are easy to leak, so as to improve the speed and accuracy of interpretation, improve the precision of identification, Enhance the effect of discontinuity

Inactive Publication Date: 2018-03-06
中国煤炭地质总局地球物理勘探研究院 +3
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  • Claims
  • Application Information

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Problems solved by technology

The two-dimensional interpretation of three-dimensional data is completed through the interpretation of two-dimensional seismic sections and the interpretation of horizontal time slices. The interpretation results are limited by the seismic and geological conditions in different regions and the experience of interpreters, resulting in the accuracy of this interpretation method. low efficiency, small structures are easy to leak, and it is difficult to find subtle structural and stratigraphic features, etc.
[0003] At present, the main problems in 2D interpretation of 3D data are: (1) Low interpretation efficiency; for huge 3D data volumes, the procedures from horizon calibration, tracking, fault interpretation, and structural map compilation are basically 2D seismic interpretation. train of thought
Therefore, unreasonable fault combinations, conflicts between upper and lower layers, and difficulty in closure are common occurrences, which require a large number of repeated revisions, which greatly affect the efficiency of interpretation
(2) It is impossible to make full use of a large amount of seismic information; whether it is manual or man-machine interpretation, due to the thinning and interpretation of the main survey line and the contact survey line, a large amount of seismic data will inevitably be unusable, so it is not possible in the process of thinning Avoid missing small faults, small structures, etc.
(3) The interpretation field of view is limited; since the interpretation is carried out on two-dimensional seismic sections or horizontal time slices, and the characteristic geological bodies are distributed in three-dimensional space, it is impossible to observe, understand and analyze such characteristic geological bodies from a three-dimensional perspective
[0004] Aiming at the problem that the above-mentioned existing 3D seismic data interpretation methods have low ability to identify small coal seam faults, no effective solution has been proposed

Method used

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  • Method and device for rapid identification of small fault of coal seam
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  • Method and device for rapid identification of small fault of coal seam

Examples

Experimental program
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Effect test

Embodiment 1

[0029] see figure 1 The flow chart of the rapid identification method of the first shown small coal seam fault; The method comprises the following steps:

[0030] Step S102, acquiring the seismic data of the set coalfield area;

[0031] Specifically, the seismic data may be 3D seismic data, 3D data volume, 3D seismic volume or 3D seismic data, etc.; the above seismic data may belong to the same geological unit, or may belong to different geological units; in order to facilitate processing and improve identification accuracy, When the seismic data above belong to different geological units, the seismic data may be divided into geological units in advance, and the different geological units are processed separately.

[0032] Step S104, performing structure-guided filtering on the seismic data;

[0033]Generally, small fault information is displayed on the event axis of coal seam reflection waves, and the above-mentioned wire filtering method will not perform smoothing processi...

Embodiment 2

[0041] see figure 2 The flow chart of the rapid identification method of the second small coal seam fault shown; the method is realized on the basis of the rapid identification method of the small coal seam fault provided in embodiment one; the method comprises the following steps:

[0042] Step S202, acquiring the seismic data of the set coalfield area;

[0043] Step S204, calculating the signal-to-noise ratio of the seismic data; determining the filter operator according to the signal-to-noise ratio;

[0044] Generally, the larger the filter operator, the rougher the filter, and the less obvious the filtering effect; and the smaller the filter operator, the more noise can be filtered out, but it is possible to filter out weak effective signals (for example, smaller faults). Therefore, in actual implementation, appropriate filter operators can be determined according to the signal-to-noise ratio of different geological units in seismic data, so as to effectively filter out ...

Embodiment 3

[0086] see image 3 The flowchart of the quick identification method of the third kind of coal seam small fault shown; This method realizes on the basis of the quick identification method of coal seam small fault that provides in embodiment one or embodiment two; The method comprises the following steps:

[0087] Step S302, acquiring the seismic data of the set coal field area;

[0088] Step S304, calculating the signal-to-noise ratio of the seismic data; determining the filter operator according to the signal-to-noise ratio;

[0089] Step S306, filter the seismic data by constructing an anisotropic diffusion smoothing algorithm and using the above filter operator;

[0090] Step S308, according to the historical seismic data of the coalfield area, set the tracking parameters of the ant body; wherein, the tracking parameters include the seed point, the angle of the foraging path, the search step size, the illegal range, the legal range, the search termination threshold and the...

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Abstract

The present invention provides a method and a device for rapid identification of a small fault of a coal seam. The method comprises the steps of: obtaining seismic data of a set coalfield region; performing structured-oriented filtering of the seismic data; employing an ant-tracking algorithm to perform processing of the filtered seismic data, and generating an ant seismic attribute data volume corresponding to the seismic data; extracting position attribute slices of a target layer in the ant seismic attribute data volume; and identifying construction of a small fault of a coal seam at the coalfield region according to the position attribute slices. On the basis of the structured-oriented filtering, the ant-tracking algorithm is employed to form the ant seismic attribute data volume underthe structured-oriented filtering; and moreover, the explanation speed and the precision of coal mine geological faults are improved by employing the mode of combining the structured-oriented filtering and the ant-tracking algorithm, and therefore, the identification fineness of the small fault of the coal seam is improved and more full and accurate geologic bases are provided for safe exploitation of the coal mine.

Description

technical field [0001] The invention relates to the technical field of geological exploration, in particular to a method and device for quickly identifying small coal seam faults. Background technique [0002] Conventional interpretation methods for 3D seismic data are usually implemented by 2D interpretation of 3D data. The two-dimensional interpretation of three-dimensional data is completed through the interpretation of two-dimensional seismic sections and the interpretation of horizontal time slices. The interpretation results are limited by the seismic and geological conditions in different regions and the experience of interpreters, resulting in the accuracy of this interpretation method. Low efficiency, low efficiency, easy leakage of small structures, and difficulty in finding subtle structural and stratigraphic features. [0003] At present, the main problems in 2D interpretation of 3D data are: (1) Low interpretation efficiency; for huge 3D data volumes, the proce...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/28G01V1/30
CPCG01V1/28G01V1/301G01V2210/642
Inventor 孟凡彬林建东郎玉泉左卫华吴建国金学良董守华杨曙光王刚陈艳鹏杨焦生
Owner 中国煤炭地质总局地球物理勘探研究院
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